OpenRaiser/Intern-Atlas huggingface dataset:
Cooperative Topology Control with Adaptation for Improved Lifetime in Wireless Sensor Networks
Venue: arXiv cs.NI 2013
Year: 2013

Topology control algorithms allow each node in a wireless multi-hop network to adjust the power at which it makes its transmissions and choose the set of neighbors with which it communicates directly, while preserving global goals such as connectivity or coverage. This allows each node to conserve energy and contribute to increasing the lifetime of the network. In this paper, in contrast to most previous work, we consider (i) both the energy costs of communication as well as the amount of available energy at each node, (ii) the realistic situation of varying rates of energy consumption at different nodes, and (iii) the fact that co-operation between nodes, where some nodes make a sacrifice by increasing energy consumption to help other nodes reduce their consumption, can be used to extend network lifetime. This paper introduces a new distributed topology control algorithm, called the Cooperative Topology Control with Adaptation (CTCA), based on a game-theoretic approach that maps the problem of maximizing the network's lifetime into an ordinal potential game. We prove the existence of a Nash equilibrium for the game. Our simulation results indicate that the CTCA algorithm extends the life of a network by more than 50% compared to the best previously-known algorithm. We also study the performance of the distributed CTCA algorithm in comparison to an optimal centralized algorithm as a function of the communication ranges of nodes and node density.
An Energy Balanced Dynamic Topology Control Algorithm for Improved Network Lifetime
Venue: arXiv cs.NI 2013
Year: 2013

In wireless sensor networks, a few sensor nodes end up being vulnerable to potentially rapid depletion of the battery reserves due to either their central location or just the traffic patterns generated by the application. Traditional energy management strategies, such as those which use topology control algorithms, reduce the energy consumed at each node to the minimum necessary. In this paper, we use a different approach that balances the energy consumption at each of the nodes, thus increasing the functional lifetime of the network. We propose a new distributed dynamic topology control algorithm called Energy Balanced Topology Control (EBTC) which considers the actual energy consumed for each transmission and reception to achieve the goal of an increased functional lifetime. We analyze the algorithm's computational and communication complexity and show that it is equivalent or lower in complexity to other dynamic topology control algorithms. Using an empirical model of energy consumption, we show that the EBTC algorithm increases the lifetime of a wireless sensor network by over 40% compared to the best of previously known algorithms.
Progressive Compression of 3D Objects with an Adaptive Quantization
Venue: arXiv cs.GR 2013
Year: 2013

This paper presents a new progressive compression method for triangular meshes. This method, in fact, is based on a schema of irregular multi-resolution analysis and is centered on the optimization of the rate-distortion trade-off. The quantization precision is adapted to each vertex during the encoding / decoding process to optimize the rate-distortion compromise. The Optimization of the treated mesh geometry improves the approximation quality and the compression ratio at each level of resolution. The experimental results show that the proposed algorithm gives competitive results compared to the previous works dealing with the rate-distortion compromise.
A Systematic Approach for Interference Alignment in CSIT-less Relay-Aided X-Networks
Venue: arXiv cs.IT 2013
Year: 2013

The degrees of freedom (DoF) of an X-network with M transmit and N receive nodes utilizing interference alignment with the support of $J$ relays each equipped with $L_j$ antennas operating in a half-duplex non-regenerative mode is investigated. Conditions on the feasibility of interference alignment are derived using a proper transmit strategy and a structured approach based on a Kronecker-product representation. The advantages of this approach are twofold: First, it extends existing results on the achievable DoF to generalized antenna configurations. Second, it unifies the analysis for time-varying and constant channels and provides valuable insights and interconnections between the two channel models. It turns out that a DoF of $\nicefrac{NM}{M+N-1}$ is feasible whenever the sum of the $L_j^2 \geq [N-1][M-1]$.
Wireless Bidirectional Relaying, Latin Squares and Graph Vertex Coloring
Venue: arXiv cs.IT 2013
Year: 2013

The problem of obtaining network coding maps for the physical layer network coded two-way relay channel is considered, using the denoise-and-forward forward protocol. It is known that network coding maps used at the relay node which ensure unique decodability at the end nodes form a Latin Square. Also, it is known that minimum distance of the effective constellation at the relay node becomes zero, when the ratio of the fade coefficients from the end node to the relay node, belongs to a finite set of complex numbers determined by the signal set used, called the singular fade states. Furthermore, it has been shown recently that the problem of obtaining network coding maps which remove the harmful effects of singular fade states, reduces to the one of obtaining Latin Squares, which satisfy certain constraints called \textit{singularity removal constraints}. In this paper, it is shown that the singularity removal constraints along with the row and column exclusion conditions of a Latin Square, can be compactly represented by a graph called the \textit{singularity removal graph} determined by the singular fade state and the signal set used. It is shown that a Latin Square which removes a singular fade state can be obtained from a proper vertex coloring of the corresponding singularity removal graph. The minimum number of symbols used to fill in a Latin Square which removes a singular fade state is equal to the chromatic number of the singularity removal graph. It is shown that for any square $M$-QAM signal set, there exists singularity removal graphs whose chromatic numbers exceed $M$ and hence require more than $M$ colors for vertex coloring. Also, it is shown that for any $2^λ$-PSK signal set, $λ\geq 3,$ all the singularity removal graphs can be colored using $2^λ$ colors.
Multipath Approach for Reliability in Query Network based Overlaid Multicasting
Venue: arXiv cs.NI 2013
Year: 2013

In Application layer multicast (ALM) also called Overlay Multicast, multicast-related functionalities are moved to end-hosts. The key advantages, overlays offers, are flexibility, adaptability and ease of deployment [1]. Application layer multicast builds a peer-to-peer (P2P) overlay multicast tree topology consisting of end-to-end unicast connections between end-hosts. End users self organize themselves into logical overlay networks for efficient data delivery. Major concern in designing ALM protocol is how to build and maintain a topology, to route data efficiently and reliably. We propose here a scheme in which the topology is built incrementally while maintaining dual feeds of the media stream to any node from the source with minimum differential delay in receiving packets from both alternatives. We have made the assumption of availability of a P2P query search network. This enables building of multicast tree directly as an overlay. There is no need of maintaining an overlaid mesh and running multicast routing protocol to maintain a multicast tree in this mesh. Thus the scheme is much more simplified than in the earlier work on multicast overlay mesh creation and management and then creation and management of multicast trees using this mesh.
ICT and Competitiveness of the Macedonian Economy
Venue: arXiv cs.CY 2013
Year: 2013

The ongoing process of liberalization, as well as the intensive technological breakthrough have a great impact either on the macroeconomic policy creators, or the dissimilarity of conventional approach to found a strategy of a certain company. Bearing in mind the very notation, core characteristics of the concept of competitiveness are needed to be explored, but also the necessity to establish a national competitiveness strategy. However, the main attention should be paid on the technological changes that affect the economic growth, but the life standard increase, as well. Nevertheless, developing and transitional economies are being down-sided with respect to the technological and innovative capability that measurably implies the necessity to redefine the conception of competitiveness. Taking into account the above clarifications, the paper will set a comparative analysis of the key factors that pressure the competitiveness of Balkans region countries, mainly by the composition of the Growth Competitiveness Index. In addition, the major accent will be put on the composite Technology index and its impact on the mainstream of the respective total index. Finally, the paper will examine the possible change of Growth Competitiveness Index ranking of the Macedonian economy, principally by the variation of the Technology index rank.
Group Learning and Opinion Diffusion in a Broadcast Network
Venue: arXiv cs.LG 2013
Year: 2013

We analyze the following group learning problem in the context of opinion diffusion: Consider a network with $M$ users, each facing $N$ options. In a discrete time setting, at each time step, each user chooses $K$ out of the $N$ options, and receive randomly generated rewards, whose statistics depend on the options chosen as well as the user itself, and are unknown to the users. Each user aims to maximize their expected total rewards over a certain time horizon through an online learning process, i.e., a sequence of exploration (sampling the return of each option) and exploitation (selecting empirically good options) steps. Within this context we consider two group learning scenarios, (1) users with uniform preferences and (2) users with diverse preferences, and examine how a user should construct its learning process to best extract information from other's decisions and experiences so as to maximize its own reward. Performance is measured in {\em weak regret}, the difference between the user's total reward and the reward from a user-specific best single-action policy (i.e., always selecting the set of options generating the highest mean rewards for this user). Within each scenario we also consider two cases: (i) when users exchange full information, meaning they share the actual rewards they obtained from their choices, and (ii) when users exchange limited information, e.g., only their choices but not rewards obtained from these choices.
To Stay Or To Switch: Multiuser Dynamic Channel Access
Venue: arXiv cs.SY 2013
Year: 2013

In this paper we study opportunistic spectrum access (OSA) policies in a multiuser multichannel random access cognitive radio network, where users perform channel probing and switching in order to obtain better channel condition or higher instantaneous transmission quality. However, unlikely many prior works in this area, including those on channel probing and switching policies for a single user to exploit spectral diversity, and on probing and access policies for multiple users over a single channel to exploit temporal and multiuser diversity, in this study we consider the collective switching of multiple users over multiple channels. In addition, we consider finite arrivals, i.e., users are not assumed to always have data to send and demand for channel follow a certain arrival process. Under such a scenario, the users' ability to opportunistically exploit temporal diversity (the temporal variation in channel quality over a single channel) and spectral diversity (quality variation across multiple channels at a given time) is greatly affected by the level of congestion in the system. We investigate the optimal decision process in this case, and evaluate the extent to which congestion affects potential gains from opportunistic dynamic channel switching.
Pathwise Performance of Debt Based Policies for Wireless Networks with Hard Delay Constraints
Venue: arXiv cs.NI 2013
Year: 2013

Hou et al have introduced a framework to serve clients over wireless channels when there are hard deadline constraints along with a minimum delivery ratio for each client's flow. Policies based on "debt," called maximum debt first policies (MDF) were introduced, and shown to be throughput optimal. By "throughput optimality" it is meant that if there exists a policy that fulfils a set of clients with a given vector of delivery ratios and a vector of channel reliabilities, then the MDF policy will also fulfill them. The debt of a user is the difference between the number of packets that should have been delivered so as to meet the delivery ratio and the number of packets that have been delivered for that client. The maximum debt first (MDF) prioritizes the clients in decreasing order of debts at the beginning of every period. Note that a throughput optimal policy only guarantees that \begin{small} $\liminf_{T \to \infty} \frac{1}{T}\sum_{t=1}^{T} \mathbbm{1}\{\{client $n$'s packet is delivered in frame $t$} \} \geq q_{i}$ \end{small}, where the right hand side is the required delivery ratio for client $i$. Thus, it only guarantees that the debts of each user are $o(T)$, and can be otherwise arbitrarily large. This raises the interesting question about what is the growth rate of the debts under the MDF policy. We show the optimality of MDF policy in the case when the channel reliabilities of all users are same, and obtain performance bounds for the general case. For the performance bound we obtain the almost sure bounds on $\limsup_{t\to\infty}\frac{d_{i}(t)}{ϕ(t)}$ for all $i$, where $ϕ(t) = \sqrt{2t\log\log t}$.
Low-Complexity Design of Generalized Block Diagonalization Precoding Algorithms for Multiuser MIMO Systems
Venue: arXiv cs.IT 2013
Year: 2013

Block diagonalization (BD) based precoding techniques are well-known linear transmit strategies for multiuser MIMO (MU-MIMO) systems. By employing BD-type precoding algorithms at the transmit side, the MU-MIMO broadcast channel is decomposed into multiple independent parallel single user MIMO (SU-MIMO) channels and achieves the maximum diversity order at high data rates. The main computational complexity of BD-type precoding algorithms comes from two singular value decomposition (SVD) operations, which depend on the number of users and the dimensions of each user's channel matrix. In this work, low-complexity precoding algorithms are proposed to reduce the computational complexity and improve the performance of BD-type precoding algorithms. We devise a strategy based on a common channel inversion technique, QR decompositions, and lattice reductions to decouple the MU-MIMO channel into equivalent SU-MIMO channels. Analytical and simulation results show that the proposed precoding algorithms can achieve a comparable sum-rate performance as BD-type precoding algorithms, substantial bit error rate (BER) performance gains, and a simplified receiver structure, while requiring a much lower complexity.
A Trust Based Fuzzy Algorithm for Congestion Control in Wireless Multimedia Sensor Networks (TFCC)
Venue: arXiv cs.NI 2013
Year: 2013

Network congestion has become a critical issue for resource constrained Wireless Sensor Networks (WSNs), especially for Wireless Multimedia Sensor Networks (WMSNs)where large volume of multimedia data is transmitted through the network. If the traffic load is greater than the available capacity of the sensor network, congestion occurs and it causes buffer overflow, packet drop, deterioration of network throughput and quality of service (QoS). Again, the faulty nodes of the network also aggravate congestion by diffusing useless packets or retransmitting the same packet several times. This results in the wastage of energy and decrease in network lifetime. To address this challenge, a new congestion control algorithm is proposed in which the faulty nodes are identified and blocked from data communication by using the concept of trust. The trust metric of all the nodes in the WMSN is derived by using a two-stage Fuzzy inferencing scheme. The traffic flow from source to sink is optimized by implementing the Link State Routing Protocol. The congestion of the sensor nodes is controlled by regulating the rate of traffic flow on the basis of the priority of the traffic. Finally we compare our protocol with other existing congestion control protocols to show the merit of the work.
Efficient Graph Algorithms for Network Analysis
Venue: arXiv cs.DS 2013
Year: 2013

The GC problem is to identify a pre-determined number of center vertices such that the distances or costs from (or to) the centers to (or from) other vertices is minimized. The bottleneck of a path is the minimum capacity of edges on the path. The Bottleneck Paths (BP) problem is to compute the paths that give us the maximum bottleneck values between pairs of vertices. The Graph Bottleneck (GB) problem is to find the minimum bottleneck value out of bottleneck paths for all possible pairs of vertices. We give two similar algorithms that are based on binary search to solve the 1-center GC problem and the GB problem on directed graphs with unit edge costs. We achieve $\tilde{O}(n^{2.373})$ worst case time complexity for both the 1-center GC problem and the GB problem, where $n$ is the number of vertices in the graph. This is better than the straightforward methods of solving the two problems in $O(n^{2.575})$ and $O(n^{2.688})$ time bounds, respectively. We then combine the Bottleneck Paths (BP) problem with the well known Shortest Paths (SP) problem to compute the shortest paths for all possible flow values. We call this problem the Shortest Paths for All Flows (SP-AF) problem. We show that if the flow demand is uncertain, but between two consecutive capacity values, the unique shortest path can be computed to push that flow. If the uncertainty stretches over two intervals, we need to prepare two shortest paths to accommodate the uncertainty, etc. In introducing this new problem, we define a new semi-ring called the distance/flow semi-ring, and show that the well known algorithm by Floyd can be used over the distance/flow semi-ring to solve the All Pairs Shortest Paths for All Flows (APSP-AF) problem.
A Review of Financial Accounting Fraud Detection based on Data Mining Techniques
Venue: arXiv cs.CY 2013
Year: 2013

With an upsurge in financial accounting fraud in the current economic scenario experienced, financial accounting fraud detection (FAFD) has become an emerging topic of great importance for academic, research and industries. The failure of internal auditing system of the organization in identifying the accounting frauds has lead to use of specialized procedures to detect financial accounting fraud, collective known as forensic accounting. Data mining techniques are providing great aid in financial accounting fraud detection, since dealing with the large data volumes and complexities of financial data are big challenges for forensic accounting. This paper presents a comprehensive review of the literature on the application of data mining techniques for the detection of financial accounting fraud and proposes a framework for data mining techniques based accounting fraud detection. The systematic and comprehensive literature review of the data mining techniques applicable to financial accounting fraud detection may provide a foundation to future research in this field. The findings of this review show that data mining techniques like logistic models, neural networks, Bayesian belief network, and decision trees have been applied most extensively to provide primary solutions to the problems inherent in the detection and classification of fraudulent data.
The Cyborg Astrobiologist: Matching of Prior Textures by Image Compression for Geological Mapping and Novelty Detection
Venue: arXiv cs.CV 2013
Year: 2013

(abridged) We describe an image-comparison technique of Heidemann and Ritter that uses image compression, and is capable of: (i) detecting novel textures in a series of images, as well as of: (ii) alerting the user to the similarity of a new image to a previously-observed texture. This image-comparison technique has been implemented and tested using our Astrobiology Phone-cam system, which employs Bluetooth communication to send images to a local laptop server in the field for the image-compression analysis. We tested the system in a field site displaying a heterogeneous suite of sandstones, limestones, mudstones and coalbeds. Some of the rocks are partly covered with lichen. The image-matching procedure of this system performed very well with data obtained through our field test, grouping all images of yellow lichens together and grouping all images of a coal bed together, and giving a 91% accuracy for similarity detection. Such similarity detection could be employed to make maps of different geological units. The novelty-detection performance of our system was also rather good (a 64% accuracy). Such novelty detection may become valuable in searching for new geological units, which could be of astrobiological interest. The image-comparison technique is an unsupervised technique that is not capable of directly classifying an image as containing a particular geological feature; labeling of such geological features is done post facto by human geologists associated with this study, for the purpose of analyzing the system's performance. By providing more advanced capabilities for similarity detection and novelty detection, this image-compression technique could be useful in giving more scientific autonomy to robotic planetary rovers, and in assisting human astronauts in their geological exploration and assessment.
The Weighted Sum Rate Maximization in MIMO Interference Networks: The Minimax Lagrangian Duality and Algorithm
Venue: arXiv cs.IT 2013
Year: 2013

We take a new perspective on the weighted sum-rate maximization in multiple-input multiple-output (MIMO) interference networks, by formulating an equivalent max-min problem. This seemingly trivial reformulation has significant implications: the Lagrangian duality of the equivalent max-min problem provides an elegant way to establish the sum-rate duality between an interference network and its reciprocal when such a duality exists, and more importantly, suggests a novel iterative minimax algorithm for the weighted sum-rate maximization. Moreover, the design and convergence proof of the algorithm use only general convex analysis. They apply and extend to any max-min problems with similar structure, and thus provide a general class of algorithms for such optimization problems. This paper presents a promising step and lends hope for establishing a general framework based on the minimax Lagrangian duality for characterizing the weighted sum-rate and developing efficient algorithms for general MIMO interference networks.